AI and Democracy: Mapping Notions, Debates and Challenges

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

Artificial intelligence (AI) is widely discussed as either a threat to democracy or a means of strengthening it. But democracy, an essentially contested concept, invokes many different levels at which AI may assist and obstruct the legitimacy of democratic government. Therefore, the aim of this review is to map how the democratic value of AI, whether positive or negative, depends on different democratic models. The review examines what there is currently no examination of: how democracy is conceptualized, what the cross-cutting patterns are, and how we should prescriptively use democracy in relation to assessing how AI supports or undermines democracy. From this, the review maps three dynamics currently at play in the literature. It shows that conceptual unclarity and pessimistic views on AI’s contribution to democracy often coincide, prescribing the need for conceptual clarity. It shows that democratic models are often “inherited” rather than reworked, prompting the need for greater engagement with how AI reshapes democratic theory. And it maps how democratic assumptions shape evaluations of AI’s democratic implications. From these results, we assess the limits of existing scholarship: without greater conceptual clarity regarding democracy, empirical findings and normative arguments risk talking past one another. Taken together, this review suggests that progress in research on democracy and AI depends not only on further empirical investigation or technical refinement, but also on sustained conceptual work that makes democratic assumptions explicit and thus open to scrutiny.